#dashboard

Orbit is an MCP-connected operations layer for Claude and other AI Agents. Connect once and every session — chats, Claude Cowork/Code/ChatGPT Codex and other agents automatically log outputs, reports and decisions to a shared dashboard. Agents read from and write to Orbit's knowledge layer, so context persists across sessions and tools without re-explaining. Includes live agent visibility, trust-weighted memory, broadcast to all agents, and agent creation. Free to start.

AgenticBI is an agentic analytics platform that turns business questions into answers.Connect BigQuery, Salesforce, SAP, Google Drive, Trino, and more. Agents understand your data, find the right datasets, join across systems, run queries, and return answers with visualizations.Or skip the question and automate the workflow entirely. "Send me a sales report every morning at 8 AM." The agent identifies the data, picks the metrics, builds the dashboard, and sets up recurring delivery to your inbox or Slack.Structured data and documents in the same query. No SQL. No analyst. Works with Claude, Cursor, VS Code, and ChatGPT. Turn on screen reader support Connects your sources, builds the semantic layer, and answers your business questions — no SQL, no analyst, no waiting.Connects your sources, builds the semantic layer, and answers your business questions — no SQL, no analyst, no waiting.

MCP server for querying Janus analytics — let your AI agent check your dashboard, events, funnels, and usage.

MCP server for MetricUI, a React dashboard component library. Gives AI coding tools access to full API references, working code examples, format suggestions, prop validation, and complete dashboard scaffolding for building analytics UIs.

Claude Code session organizer — dashboard MCP server to manage, search, archive and organize your Claude Code conversations and projects.

MCP server + CLI that scans any project to discover its full AI ecosystem: MCP servers, context files, skills, agents, memories, and configurations for 19+ AI tools (Claude, Cursor, Windsurf, Copilot, Gemini, Codex, and more). Generates interactive HTML dashboards and supports ecosystem export/import across tools.

Full-featured MCP server for Apache Superset with 135+ tools for dashboards, charts, datasets, SQL Lab, security, and more

MCP server for Lightdash analytics platform. Enables AI assistants like Claude to discover data, execute queries, create charts, and manage dashboards programmatically. Supports Lightdash Cloud and self-hosted instances.

AI data intelligence platform that brings your data warehouse, dashboards, monitoring, and accumulated business knowledge into any MCP client. Connects to BigQuery, Snowflake, PostgreSQL, MySQL, ClickHouse, Redshift, Databricks, SQL Server, and Azure Synapse.

MCP App that renders interactive Chart.js charts and dashboards inline in AI conversations. Supports bar, line, area, pie, doughnut, scatter, and radar charts with multi-chart dashboard grids.

Query bank transactions and invoices, manage financial contacts directly from your LLM. Well transforms your AI assistant into a comprehensive financial insight and automation system, an AI-powered finance agent that connects multiple banking APIs, categorizes expenses, and generates real-time financial insights. Perfect for SMB founders and finance teams who want to eliminate manual bookkeeping & customize FP&A and investor reporting. Access live banking data, automate invoice workflows, and get intelligent financial analysis without switching between multiple tools.

Fabi is a sophisticated analyst agent that independently handles data analysis tasks. Simply delegate tasks in natural language - Fabi will autonomously: - Discover and inspect schemas using RAG - Find relevant tables/columns with semantic understanding - Generate and validate SQL/Python code - Execute queries with error handling - Format and preview results

The Next generation MCP toolkit

让AI助手直接分析你的Grafana监控数据 - A Model Context Protocol server for Grafana data analysis

MCP server to help with chat and dashboard creation. ✅ One consistent framework for charts and dashboards with one common design language. ✅ Validated config output that is readable and easy to alter or maintain. ✅ Live preview of the dashboard to iterate the design until the dashboard is perfect. ✅ Use of local or remote datasets simply by providing a path or URL.

AI Agents to support sustainable spending on Bunq using MCP servers